The formula for percent error is: 

$\displaystyle \frac{\left | \text{Accepted Value - Measured Value}\right |}{\text{Accepted Value}} \times100\%$

In this case, the measured value is 12.8g and the accepted value is 32.9g.

$\displaystyle \frac{\left | 32.9g-12.8g\right |}{32.9g}\times 100\%=61\%$

To find percent error we need to use the following equation:

$\displaystyle \frac{\text{theoretical yield}-\text{actual yield}}{\text{theoretical yield}}*100\%$

Plug in 42 for the theoretical yield and 32.73 for the actual yield and solve accordingly.

$\displaystyle \frac{42g-32.73g}{42g}*100\%=22.07\%$

To find the percent error we need to use the following equation:

$\displaystyle \frac{\text{theoretical yield}-\text{actual yield}}{\text{theoretical yield}}*100\%$

But in order to do this, we first have to convert moles of sodium oxide into grams:

$\displaystyle 4 mol\ Na_{2}O * \frac{62g}{1 mol}=248g\ NaO_2$

This gives us a theoretical yield of 248g, which we plug in with our 195g actual yield.

$\displaystyle \frac{248g-195g}{248g}*100\%=21.37\%\ \text{error}$

Our first step to complete this problem is to convert moles AgF into grams:

$\displaystyle 0.6 mol\ AgF*\frac{127g}{1 mol}=76.2g\ AgF$

This gives us a theoretical yield of 76.2 grams. We can find the percent error by plugging in 76.2g for our theoretical yield and 43g for the actual yield in the following equation:

$\displaystyle \frac{\text{theoretical yield}-\text{actual yield}}{\text{theoretical yield}}*100\%$

$\displaystyle \frac{76.2g-43g}{76.2g}*100\%=43.57\%\ \text{error}$

This bag is accurate because it provided the correct number of balloons, however, the process is not precise as the results were clearly not repeatable.

Accuracy deals with how close the measurement got to the accepted measurement. Precision deals with how consistent the measurement is. The bag with 100 balloons inside matched the claim made on the bag, meaning it was accurate. It was not precise because the other measurements show that the number of balloons is variable.

Precision measures is how consistently a device records the same answer. In this case, Michael's scale is ALWAYS $\displaystyle 2kg$ short. Even though it displays the wrong value, it is consistent. That means it is precise. Measuring a $\displaystyle 10kg$ object will always display a mass of $\displaystyle 8kg$; the results are easily reproduced.

Accuracy is how well a device measures something against its accepted value. In this case, Michael's scale is not accurate because it is always off by $\displaystyle 2kg$.

The claim for the mass of the first bag is accurate; the brand says there should be $\displaystyle 25.5g$ in each bag and there was $\displaystyle 25.5g$ in the first bag.

The claim on the first bag is not precise, as the results are not replicated universally throughout the experiment. The masses of the bags fluctuate, with the average of all three bags equal to $\displaystyle \small 25.7g$.

Accuracy is measured as the degree of closeness to the actual measurement. In our case, accurate shots will hit the bullseye. Precision is measured as the degree of closeness of one measurement to the next. In our case, precise shots will be clustered together.

To get high accuracy but low precision, measurements must center around the target value but be variable. The bowman's arrows will not be clustered (low precision), but will be accurately distributed around the bullseye. If all the shots were averaged, the bullseye would be at the center.

Precision is a measure of reproducibility. If multiple trials produce the same result each time with minimal deviation, then the experiment has high precision. This is true even if the results are not true to the theoretical predictions; an experiment can have high precision with low accuracy.

In contrast, accuracy is the measure of difference between a calculated value and the true value of a measurement. High accuracy demands that the experimental result be equal to the theoretical result.

An archer hitting a bulls-eye is an example of high accuracy, while an archer hitting the same spot on the bulls-eye three times would be an example of high precision.

Accuracy is the measure of difference between a calculated value and the true value of a measurement. High accuracy demands that the experimental result be equal to the theoretical result.

In contrast, precision is a measure of reproducibility. If multiple trials produce the same result each time with minimal deviation, then the experiment has high precision. This is true even if the results are not true to the theoretical predictions; an experiment can have high precision with low accuracy.

An archer hitting a bulls-eye is an example of high accuracy, while an archer hitting the same spot on the bulls-eye three times would be an example of high precision.